Transcript EECS at UC Berkeley

Next Century Challenges for
Computer Science and
Electrical Engineering
Professor Randy H. Katz
United Microelectronics Corporation
Distinguished Professor
CS Division, EECS Department
University of California, Berkeley
Berkeley, CA 94720-1776 USA
Agenda
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The Information Age
EECS Department at Berkeley
Student Enrollment Pressures
Random Thoughts and Recommendations
Summary and Conclusions
Agenda
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The Information Age
EECS Department at Berkeley
Student Enrollment Pressures
Random Thoughts and Recommendations
Summary and Conclusions
A Personal Historical View
• 20th Century as “Century of the Electron”
– 1884: Philadelphia Exposition--Rise of EE as a profession
– 1880s: Electricity harnessed for communications, power, light,
transportation
– 1890s: Large-Scale Power Plants (Niagara Falls)
– 1895: Marconi discovers radio transmission/wireless telegraphy
– 1905-1945: Long wave/short wave radio, television
– 1900s-1950s: Large-scale Systems Engineering (Power, Telecomms)
– 1940s-1950s: Invention of the Transistor & Digital Computer
– 1960s: Space program drives electrical component minaturization
– 1970s: Invention of the Microprocessor/rise of microelectronics
– 1980s-1990s: PCs and data communications explosion
• Power Engineering --> Communications --> Systems
Engineering --> Microelectronics --> ???
Late 20th Century Rise of the
“Information Age”
• Electronics + computing = “information technology”
• Technologies crucial for manipulating large amounts of
information in electronic formats
– Hardware: Semiconductors, optoelectronics, high performance
computing and networking, satellites and terrestrial wireless
communications devices;
– Software: Computer programs, software engineering, software
agents;
– Hardware-Software Combination: Speech and vision recognition,
compression technologies;
• Information industries: assemble, distribute, and
process information in a wide range of media, e.g.,
telephone, cable, print, and electronic media companies
• $3 trillion world wide industry by 2010
Software Jobs Go Begging
• “America’s New Deficit: The Shortage of
Information Technology Workers,”
Department of Commerce
– Job growth exceeds the available talent
– 1994-2005: 1 million new information technology workers
will be needed
• “Help Wanted: The IT Workforce Gap at the
Dawn of a New Century,” ITAA
– 190,000 unfilled positions for IT workers nationwide
– Between 1986 and 1994, bachelor degrees in CS fell from
42,195 to 24,200 (43%)
Robert Lucky’s Inverted Pyramid
Information
Technology
Applications Software
Software
Middleware Software
Algorithms
Embedded Software
System Software
FPGA Design
VLSI Design
Circuit Design
Hardware
Device Design
Process
Design
Physics
Increasing Numbers
of Practitioners
Technology
Agenda
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The Information Age
EECS Department at Berkeley
Student Enrollment Pressures
Random Thoughts and Recommendations
Summary and Conclusions
Departmental Culture
• A shared view of computing joining mathematics and
physics as core of the sciences and engineering
• Large-scale interdisciplinary experimental research
projects with strong industrial collaborations
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Architecture: RISC, RAID, NOW, IRAM, CNS-1, BRASS
Parallel Systems: Multipole, ScaLAPACK, Spilt-C, Titanium
Berkeley Digital Library Project: Environmental Data
InfoPad: Portable Multimedia Terminal for Classroom Use
PATH Intelligent Highway Project, FAA Center of Excellence
• Computation and algorithmic methods in EE
– Circuit Simulation, Process Simulation, Optical Lithography
– CAD Synthesis/Optimization, Control Systems
• Increasing collaboration with other departments in
Engineering and elsewhere on campus
Historical Perspective
• Early-mid 1950s: Computer engineering activity grows within EE
department
• Early 1960s: Separate CS Department formed within College of
Letters and Science
• Early 1970s: Forced merger--semi-autonomous CS Division
within single EECS Department; separate L&S CS program for
undergraduates continues
• 1980s: Strong collaborations between EE and CS in VLSI, CAD
• 1990s: Increasing interactions between EE systems/CS
AI/vision; EE comms/CS networking/distributed systems;
Intelligent Systems/Hybrid Control Systems
• 1994-Present: Very rapid growth in CS enrollments
• 1996-1999: First CS Department Chair; Goal to make symmetric
the relationship between EE and CS
Departmental Structure
Cory Hall
EE Devices
and Circuits
Physical
Systems
EE Signals
and Systems
Electrical
Engineering
Computer
Science
Computer
Science
Soda Hall
What happens to
faculty who work
at the intersections?
EE/CS
Faculty FTE Breakdown
• EE
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• CS
Signal Processing: 4.5
Communication: 3.0
Networks: 2.5
CAD: 3.5
ICs: 5.0
Solid State & MEM’s: 4.5
Process Tech. & Man.: 5.0
Optoelectronics: 5.0
EM & Plasma: 2.25
Controls: 3.0
Robotics: 2.0
Bioelectronics: (1.3)
Power: 1.5
TOT: 40.75 (+1.3 P-in-R)
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Sci Comp: 2.5
Architecture: 5.0
Software: 5.5
Theory: 6.0
OS/Nets: 4.5
MM/UI/Graphics: 4.0
AI: 5.5
DB: 2.0
TOT: 35 + 2 SOE Lecturers
– DEPARTMENT: 77.75 FTE
83.75 Authorized (2000)
3 New + 2 Continue
Agenda
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The Information Age
EECS Department at Berkeley
Student Enrollment Pressures
Random Thoughts and Recommendations
Summary and Conclusions
UG Degree History at Berkeley
#Degrees
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0
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142
BA
BS
About
243
half are
CS degrees
286
81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97
Year
Undergraduate Enrollment Trends
1400
1200
1000
Total
800
600
400
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EECS/EE
CS Total
EECS/CS
L&S CS
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The trend towards CS enrollment growth continues
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A New Vision for EECS
“If we want everything to stay
as it is, it will be necessary for
everything to change.”
Giuseppe Tomasi Di Lampedusa (1896-1957)
Old View of EECS
EE
physics
circuits
signals
control
Physical
World
CS
algorithms
programming
comp systems
AI
Synthetic
World
New View of EECS
Intelligent Sys & Control
Communications Sys
Intelligent Displays
EECS
complex/electronics
systems
Signal Proc
Control
EE
Processing
Devices
MEMS
Optoelectronics
Circuits
AI
Software
Robotics/Vision
InfoPad
IRAM
components
CAD
Sim & Viz
Reconfigurable Systems
Computing Systems
Multimedia
User Interfaces
CS
algorithms
Programming
Databases
CS Theory
MechE
Sensors &
Control
Physical
Sciences/
Electronics
Materials
Science/
Electronic
Materials
Design
Sci
Info Mgmt
& Systems
EECS
BioSci/Eng
Biosensors &
BioInfo
Cognitive
Science
Computational
Sci & Eng
Observations
• Introduction to Electrical Engineering course
is really introduction to devices and circuits
• Freshman engineering students extensive
experience with computing; significantly less
experience with physical systems (e.g., ham
radio)
• Insufficient motivation/examples in the early
EE courses; excessively mathematical and
quantitative
• These factors drive students into the CS
track
Curriculum Redesign
• EECS 20: Signals and Systems
• Every EECS student will take:
– Introduction to Signals and Systems
– Introduction to Electronics
– Introduction to Computing (3 course sequence)
• Computing emerges as a tool as important as
mathematics and physics in the engineering
curriculum
– More freedom in selecting science and mathematics courses
– Biology becoming increasing important
EECS 20: Structure and
Interpretation of Systems and Signals
• Course Format: Three hours of lecture and three hours
of laboratory per week.
• Prerequisites: Basic Calculus.
• Introduction to mathematical modeling techniques used
in the design of electronic systems. Applications to
communication systems, audio, video, and image
processing systems, communication networks, and
robotics and control systems. Modeling techniques that
are introduced include linear-time-invariant systems,
elementary nonlinear systems, discrete-event systems,
infinite state space models, and finite automata.
Analysis techniques introduced include frequency
domain, transfer functions, and automata theory. A
Matlab-based laboratory is part of the course.
Topics Covered
• Sets
• Signals
– Image, Video, DTMF, Modems,
Telephony
• Predicates
– Events, Networks, Modeling
• Frequency
– Audio, Music
• Linear Time Invarient
Systems
• Filtering
– Sounds, Images
• Convolution
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Transforms
Sampling
State
Composition
Determinism
State Update
Examples
– Modems, Speech models,
Audio special effects, Music
EE 40: Introduction to
Microelectronics Circuits
• Course Format: Three hours of lecture, three
hours of laboratory, and one hour of discussion
per week.
• Prerequisites: Calculus and Physics.
• Fundamental circuit concepts and analysis
techniques in the context of digital electronic
circuits. Transient analysis of CMOS logic
gates; basic integrated-circuit technology and
layout.
CS 61A: The Structure and
Interpretation of Computer Programs
• Course Format: 3 hrs lecture, 3 hrs discussion, 2.5 hrs
self-paced programming laboratory per week.
• Prerequisites: Basic calculus & some programming.
• Introduction to programming and computer science.
Exposes students to techniques of abstraction at several
levels: (a) within a programming language, using higherorder functions, manifest types, data-directed
programming, and message-passing; (b) between
programming languages, using functional and rule-based
languages as examples. It also relates these to practical
problems of implementation of languages and algorithms
on a von Neumann machine. Several significant
programming projects, programmed in a dialect of LISP.
CS 61B: Data Structures
• Course Format: 3 hrs lecture, 1 hr discussion, 2
hrs of programming lab, average of 6 hrs of selfscheduled programming lab per week.
• Prerequisites: Good performance in 61A or
equivalent class.
• Fundamental dynamic data structures, including
linear lists, queues, trees, and other linked
structures; arrays strings, and hash tables.
Storage management. Elementary principles of
software engineering. Abstract data types.
Algorithms for sorting and searching.
Introduction to the Java programming language.
CS 61C: Machine Structures
• Course Format: 2 hrs lecture, 1 hr discussion,
average of six hrs of self-scheduled programming
laboratory per week.
• Prerequisites: 61B.
• The internal organization and operation of digital
computers. Machine architecture, support for
high-level languages (logic, arithmetic, instruction
sequencing) and operating systems (I/O,
interrupts, memory management, process
switching). Elements of computer logic design.
Tradeoffs involved in fundamental architectural
design decisions.
Five Undergraduate Programs
• Program I: Electronics
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Electronics
Integrated Circuits
Physical Electronics
Micromechanical Systems
• Program II: Communications, Networks, Systems
– Computation
– Bioelectronics
– Circuits and Systems
• Program III: Computer Systems
• Program IV: Computer Science
• Program V: General
Agenda
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The Information Age
EECS Department at Berkeley
Student Enrollment Pressures
Random Thoughts and Recommendations
Summary and Conclusions
Department’s Strategic Plan
• Human Centered Systems
– User Interfaces: Image,
graphics, audio, video,
speech, natural language
– Information Management &
Intelligent Processing
– Embedded and Networkconnected computing
» Hardware building blocks:
DSP, PGA, Comms
» High performance, low
power devices, sensors,
actuators
» OS and CAD
» Ambient/Personalized/
Pervasive Computing
• “Software” Engineering
– Design, development,
evolution, and maintenance
of high-quality complex
software systems
» Specification &
verification
» Real time software
» Scalable algorithms
» Evolution & maintenance
of legacy code
21st Century Challenge for
Computer Science
• Avoid the mistakes of academic Math departments
– Mathematics pursued as a “pure” and esoteric discipline for its
own sake (perhaps unlikely given industrial relevancy)
– Faculty size dictated by large freshman/sophomore program (i.e.,
Calculus teaching) with relatively few students at the
junior/senior level
– Other disciplines train and hire their own applied mathematicians
– Little coordination of curriculum or faculty hiring
• Computer Science MUST engage with other
departments using computing as a tool for their
discipline
– Coordinated curriculum and faculty hiring via cross-departmental
coordinating councils
21st Century Challenges for
Electrical Engineering
• Avoid the trap of Power Systems Engineering
– Student interest for EE physical areas likely to continue their
decline (at least in the USA), just when the challenges for new
technologies becoming most critical
» Beginning to see the limits of semiconductor technology?
» What follows Silicon CMOS? Quantum dots? Cryogenics?
Optical computation? Biological substrates? Synthesis of
electrical and mechanical devices beyond transistors
(MEMS/nanotechnology)
» Basic technology development, circuit design and production
methods
• Renewed emphasis on algorithmic and mathematical
EE: Signal Processing, Control, Communications
– More computing systems becoming application-specific
– E.g., entertainment, civilian infrastructure (air traffic control), …
21st Century Challenges for
EE and CS
• 21st Century to be “Century of Biotechnology”?
– Biomimetics: What can we learn about building complex systems
by mimicing/learning from biological systems?
» Hybrids are crucial in biological systems; Never depend on a
single group of software developers!
» Reliability is a new metric of system performance
– Human Genome Project
» Giant data mining application
» Genome as “machine language” to be reverse engineered
– Biological applications of MEMS technology: assay lab-on-a-chip,
molecular level drug delivery
– Biosensors: silicon nose, silicon ear, etc.
• What will be more important for 21st century
engineers to know: more physics or more biology?
Example: Affymetrix
www.affymetrix.com
• Develops chips used in the acquisition, analysis,
& management of genetic information for
biomedical research, genomics, & clinical
diagnostics
• GeneChip system: disposable DNA probe
arrays containing specific gene sequences,
instruments to process the arrays, &
bioinformatics software
• IC company?
Software company?
Bioengineering company?
Biotech company?
Should EE and CS Be Separate
Departments?
• EEs need extensive computing: will spawn
competing Computer Engineering activity anyway
• Much productive collaborative at intersection of
EE and CS: CAD, Architecture, Signal Processing,
Control/Intelligent Systems, Comms/Networking
• But all quantitative fields are becoming as
computational as EE; e.g., transportation systems
in CivilEng
• Will natural center of gravity of CS move towards
cognitive science, linguistics, economics, biology?
Agenda
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The Information Age
EECS Department at Berkeley
Student Enrollment Pressures
Random Thoughts and Recommendations
Summary and Conclusions
Summary and Conclusions
• Fantastic time for the IT fields of EE and CS
– As we approach 2001, we are in the Information Age,
not the Space Age!
– BUT, strong shift in student interest from the physical
side of EE towards the algorithmic side of CS
• Challenge for CS
– Avoid mistakes of math as an academic discipline
– Coordinate with other fields as they add computing
expertise to their faculties
• Challenge for EE
– What will be the key information system implementation
technology of 21st century?
• Challenge for EE and CS
– How to contribute to the Biotech revolution of the next century